A county-level estimate of PM(2.5) related chronic mortality risk in China based on multi-model exposure data

基于多模型暴露数据的中国PM2.5相关慢性死亡风险县级评估

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Abstract

BACKGROUND: Ambient fine particulate matter (PM(2.5)) pollution is currently a serious environmental problem in China, but evidence of health effects with higher resolution and spatial coverage is insufficient. OBJECTIVE: This study aims to provide a better overall understanding of long-term mortality effects of PM(2.5) pollution in China and a county-level spatial map for estimating PM(2.5) related premature deaths of the entire country. METHOD: Using four sets of satellite-derived PM(2.5) concentration data and the integrated exposure-response model which has been employed by the Global Burden of Disease (GBD) to estimate global mortality of ambient and household air pollution in 2010, we estimated PM(2.5) related premature mortality for five endpoints across China in 2010. RESULT: Premature deaths attributed to PM(2.5) nationwide amounted to 1.27million in total, and 119,167, 83,976, 390,266, 670,906 for adult chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, and stroke, respectively; 3995 deaths for acute lower respiratory infections were estimated in children under the age of 5. About half of the premature deaths were from counties with annual average PM(2.5) concentrations above 63.61μg/m(3), which cover 16.97% of the Chinese territory. These counties were largely located in the Beijing-Tianjin-Hebei region and the North China Plain. High population density and high pollution areas exhibited the highest health risks attributed to air pollution. On a per capita basis, the highest values were mostly located in heavily polluted industrial regions. CONCLUSION: PM(2.5)-attributable health risk is closely associated with high population density and high levels of pollution in China. Further estimates using long-term historical exposure data and concentration-response (C-R) relationships should be completed in the future to investigate longer-term trends in the effects of PM(2.5).

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